Arun Singh Bhadwal

Assistant Professor Arun Singh Bhadwal is currently engaged in conducting research focused on the design of drug molecules employing data-assisted techniques derived from deep learning. He has proposed an innovative approach for representing molecules, specifically addressing challenges associated with branches and rings in the SMILES representation. Additionally, Asst. Professor Bhadwal is actively involved in studying the architecture of variational autoencoders and has devised a solution to tackle the problem of posterior collapse.

Prior to joining UPES, Assistant Professor Bhadwal pursued his Doctor of Philosophy at the esteemed National Institute of Technology Uttarakhand. Preceding this, he served as a Lecturer at the University of Jammu for a duration of three years.

Drug Design I Recurrent Neural Network I Variational Autoencoder I Conditional VAE I Bayesian Optimization.

Assistant Prof. Bhadwal’s teaching philosophy is grounded in the understanding that it is his responsibility to create a climate that supports and encourages student learning. He has incorporated some elements of “flipping the classroom” into his classes such as pre-reading assignments, in which students read assigned sections of the textbook and/or other resources prior to coming to class where they complete a short quiz. Quiz material is not repeated in class but instead is used as the foundation for in-class assignments that involve students working with real data and situations. Using authentic problems helps students move from novice to expert thinking.

Assistant Prof. Bhadwal has served as an esteemed educator, imparting valuable knowledge to master's level students in the fields of Compiler Design, Operating System, and Database Management System. Within the Compiler Design course, I extensively elucidated the significance and functionalities of each layer within the compiler structure. In the Operating System course, I provided comprehensive explanations of the intricate aspects of process and memory management. Moreover, in the DBMS course, I facilitated in-depth discussions on the techniques of normalization and diverse methods of concurrency control. Through my diligent teaching, I have strived to equip students with a strong foundation in these critical subjects.

Dr. Arun has published many articles and conference papers in national and international journals in the field of computer vision and machine learning.

Some prominent are listed below-

Journal Publications (SCI/SCIE)

Bhadwal, Arun Singh, Kamal Kumar, and Neeraj Kumar. "GenSMILES: An enhanced validity conscious representation for inverse design of molecules." Knowledge-Based Systems 268 (2023): 110429. SCI, Impact Factor: 8.16

Bhadwal, Arun Singh, Kamal Kumar, and Neeraj Kumar. ”GMG-NCDVAE: Guided de novo Molecule Generation using NLP Techniques and Constrained Diverse Variational Autoencoder.” ACM Transactions on Asian and Low-Resource Language Information Pro-cessing, 2023. SCI, Impact Factor: 2.18

Conference Publications:

Bhadwal, Arun Singh, and Kamal Kumar. "Direct De Novo Molecule Generation Using Probabilistic Diverse Variational Autoencoder." Computer Vision and Machine Intelligence: Proceedings of CVMI 2022. Singapore: Springer Nature Singapore, 2023. 13-22.

Bhadwal, Arun Singh, and Kamal Kumar. "GVA: Gated Variational Autoencoder for de novo molecule generation." 2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON). IEEE, 2022.

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